Learn the fundamentals of Bayesian statistics and how it differs from frequentist approaches. Understand priors, likelihoods, and posterior distributions.
Tutorial series
R Bayesian Stats
4 tutorials — follow in order for the best learning path.
- Introduction to Bayesian Thinking
- Getting Started with brms
Learn how to fit Bayesian regression models in R using the brms package. Covers basic syntax, model fitting, and interpreting results.
- Prior Selection in Bayesian Models
Learn how to choose appropriate prior distributions for Bayesian models in R. Covers prior types with practical brms examples.
- Posterior Predictive Checks for Model Validation in R
Learn how to perform posterior predictive checks to validate your Bayesian models in R using brms and bayesplot.